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Characterization of a mine fire using atmospheric monitoring system sensor data

机译：使用大气监测系统传感器数据表征矿井火灾

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摘要

Atmospheric monitoring systems (AMS) have been widely used in underground coal mines in the United States for the detection of fire in the belt entry and the monitoring of other ventilation-related parameters such as airflow velocity and methane concentration in specific mine locations. In addition to an AMS being able to detect a mine fire, the AMS data have the potential to provide fire characteristic information such as fire growth - in terms of heat release rate - and exact fire location. Such information is critical in making decisions regarding fire-fighting strategies, underground personnel evacuation and optimal escape routes. In this study, a methodology was developed to calculate the fire heat release rate using AMS sensor data for carbon monoxide concentration, carbon dioxide concentration and airflow velocity based on the theory of heat and species transfer in ventilation airflow. Full-scale mine fire experiments were then conducted in the Pittsburgh Mining Research Division's Safety Research Coal Mine using an AMS with different fire sources. Sensor data collected from the experiments were used to calculate the heat release rates of the fires using this methodology. The calculated heat release rate was compared with the value determined from the mass loss rate of the combustible material using a digital load cell. The experimental results show that the heat release rate of a mine fire can be calculated using AMS sensor data with reasonable accuracy.
机译：大气监测系统（AMS）已广泛应用于美国的地下煤矿，用于检测皮带入口处的火灾，并监测特定矿井位置的气流速度和甲烷浓度等其他通风相关参数。除了AMS能够探测到矿井火灾外，AMS数据还有可能提供火灾特征信息，例如火灾增长（在热释放率方面）和准确的火灾位置。这些信息对于制定有关灭火策略、地下人员疏散和最佳逃生路线的决策至关重要。本研究基于通风气流中的热量和物质传递理论，开发了一种利用AMS传感器数据计算一氧化碳浓度、二氧化碳浓度和气流速度的火灾热释放速率的方法。然后，在匹兹堡采矿研究部的安全研究煤矿使用具有不同火源的AMS进行了全面的矿井火灾实验。从实验中收集的传感器数据用于使用这种方法计算火灾的热释放率。将计算出的热释放率与使用数字称重传感器根据可燃材料的质量损失率确定的值进行比较。实验结果表明，利用AMS传感器数据可以合理准确地计算出矿井火灾的放热速率。

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